What Are Some Real World Applications of Agentic AI?

Agentic AI represents a major leap beyond traditional AI by not just responding to commands but actively making decisions, setting goals, and taking actions to achieve them. 

In this post, we’ll explore how businesses across industries are using agentic AI in real-world scenarios. 

Whether you’re exploring innovation for your company or just curious about how this emerging technology delivers value, read on to see what agentic AI can do in real business environments.

What is agentic AI?

Agentic AI, also known as AI agents, refers to systems that can operate more independently than traditional AI. Instead of just analysing data or answering questions, these agents are designed to pursue goals, make decisions, and take action without needing constant human input.

At a basic level, agentic AI works by combining several core components: a planning engine to break down goals, a reasoning system to make decisions, a memory to retain context, and the ability to interact with other software or services. Together, these elements allow the AI to operate more like a collaborator than a tool.

Key characteristics of agentic AI

Here are some of its defining characteristics:

• Goal-driven – can set and work toward objectives without needing constant prompts.
• Autonomous – acts independently to complete tasks from start to finish.
• Context-aware – remembers past interactions to make smarter, more relevant decisions.
• Multi-step reasoning – handles complex workflows by breaking them into logical steps.
• Self-improving – learns from feedback and results to get better over time.
• System-integrated – connects with APIs, databases, and apps to carry out actions.

Difference between agentic AI and traditional AI

Traditional AI is great at doing specific tasks when given clear instructions. It can answer questions, generate content, recognise patterns, or classify data, but only when prompted. 

Agentic AI, on the other hand, is built to take initiative. Instead of waiting for commands, it can define goals, make decisions, and act on its own to achieve results. It doesn’t just respond, it plans, executes, and adapts.

Here’s a practical comparison to make it clearer:

• Traditional AI might help you write a product description if you give it a prompt.
• Agentic AI could look at your inventory, find a missing product description, write it, upload it to your system, and notify the team, all without you asking.

Another big difference is adaptability. Traditional AI often struggles when conditions change or when it hits an unexpected scenario. Agentic AI is built with reasoning, memory, and autonomy, so it can adjust its behaviour mid-task and keep working toward its goal, more like a human would.

Here’s a comparison table that highlights the key differences between traditional AI and agentic AI:

Real world applications of agentic AI across industries

Agentic AI isn’t just a futuristic concept; it’s already at work in real businesses today. Let’s take a look at how different industries are using agentic AI. 

Healthcare

Agentic AI is beginning to transform healthcare by not just assisting professionals but actively managing tasks, coordinating care, and improving efficiency. Here’s how it’s being used in practical ways:

1. Clinical workflow automation

AI agents can now take over repetitive and time-sensitive tasks in clinical workflows. For example, instead of a staff member manually checking which patients need follow-ups, an agentic system can scan medical records, flag patients due for appointments, schedule those visits, and send reminders, all automatically.

2. Personalised treatment support

In chronic disease management and long-term care, agentic AI can monitor patient data over time, such as blood sugar levels, blood pressure, or lab results, and recommend personalised adjustments to treatment plans.

For instance, an AI agent might detect a gradual rise in blood pressure and suggest a medication review or prompt a doctor to check in with the patient. It can also message patients with reminders, tips, or early warnings, helping them stay engaged in their own care.

3. Administrative task management

Healthcare providers spend a significant amount of time on paperwork, including referrals, billing codes, insurance pre-authorisations, and other administrative tasks.

Agentic AI can take the lead on these tasks by gathering the necessary information, filling out forms, submitting requests, and tracking responses across systems.

This kind of behind-the-scenes automation doesn’t just save time, it reduces errors and delays that can affect patient care.

4. Hospital operations and resource coordination

Inside hospitals, agentic AI is being used to manage logistics in real time. It can track bed availability, assign rooms based on patient needs, manage the use of medical equipment, and even optimise staff schedules depending on shifts, emergencies, or patient load.

Finance

Finance is one of the industries where speed, accuracy, and adaptability are absolutely critical, making it a perfect match for agentic AI. 

1. Intelligent financial advisors

Agentic AI can act as a proactive financial assistant for both individuals and institutions. Instead of waiting for a user to ask for advice, these agents can monitor portfolio performance, track market trends, and automatically suggest rebalancing strategies based on risk tolerance and goals.

For wealth management firms, AI agents can flag anomalies, adjust allocations, or generate personalised reports, helping advisors deliver more value without being bogged down in manual analysis.

2. Automated compliance and risk monitoring

Staying compliant with financial regulations is an ongoing challenge. Agentic AI can help by constantly scanning transactions, communications, and logs for compliance issues or signs of fraud.

Unlike traditional systems that wait for specific rule-based alerts, agentic AI can adapt its approach, refine its monitoring criteria over time, and even take pre-emptive actions like freezing a suspicious account or escalating a risk case for review.

3. Loan and credit decision automation

In lending, agentic AI can handle more than just scoring applications. It can assess financial history, cross-reference third-party data, suggest personalised loan products, request additional documentation, and even follow up with applicants automatically.

This end-to-end process automation reduces approval times, improves accuracy, and enhances the borrower experience, especially at scale.

4. Customer support and service operations

AI agents in finance can serve as digital representatives, handling common service requests like balance inquiries, transaction disputes, or payment updates. But they go further than chatbots.

An agentic AI can resolve issues across systems (e.g., reverse a charge, update account info, send confirmation emails), follow up with the customer, and escalate to a human when truly needed. It’s capable of completing tasks, not just answering questions.

5. Fraud detection and response

Fraud detection is a moving target, and agentic AI is well-equipped to keep up. These agents can learn from past fraud patterns, track suspicious activity in real time, and initiate a chain of actions: flagging a transaction, notifying the customer, locking the account, and generating a report for compliance, all autonomously.

E-commerce and retail

In e-commerce and retail, customer expectations are sky-high, and businesses need to move fast to keep up. Agentic AI is stepping in as a behind-the-scenes powerhouse.

1. Personalised shopping experiences

Agentic AI can go beyond static product recommendations. These AI agents actively analyse customer behaviour, preferences, and purchase history to create dynamic, real-time shopping journeys.

For example, an agent might notice a customer browsing running shoes, suggest complementary products (like socks or a fitness tracker), apply a personalised discount, and even follow up via email if they abandon their cart.

2. Inventory and supply chain optimisation

Managing inventory can be a logistical headache. Agentic AI helps by predicting demand, identifying stock shortages, and triggering automatic reorders or supplier communications.

Let’s say a certain product is trending upward. An AI agent can detect the spike, alert the warehouse, reallocate stock from slower-moving locations, and coordinate restocking, all while keeping stakeholders informed.

3. Customer service automation

Customer service is often a bottleneck, but agentic AI is changing that. Instead of waiting for a rep, customers can interact with AI agents that don’t just answer questions, but actually solve problems.

Need to return an item? An AI agent can process the request, generate a return label, issue a refund, and update the customer, all within minutes. It can also follow up to ensure satisfaction or offer a discount to encourage a repeat purchase.

4. Marketing and campaign management

Agentic AI can take over the planning and execution of marketing campaigns. It can segment audiences, test messaging, monitor engagement in real time, and adjust ad spend on the fly.

For example, during a product launch, an AI agent might identify which customer segments are responding best, shift focus toward those groups, and scale back underperforming channels, all without waiting for a marketer to pull the data and make changes manually.

5. Pricing and promotion optimisation

Retail pricing is a delicate balance. Agentic AI can monitor competitor prices, track sales trends, and automatically adjust pricing or apply time-sensitive promotions to maximise profit or clear inventory.

Manufacturing

Manufacturing is all about precision, timing, and coordination. That’s exactly where agentic AI shines, by taking on complex, multi-step tasks and keeping operations running smoothly without constant human oversight.

1. Predictive maintenance and equipment monitoring

Agentic AI is a game-changer for keeping machines running efficiently. Instead of waiting for breakdowns, AI agents continuously monitor equipment data (like temperature, vibration, or energy usage) and predict when maintenance is needed.

When an issue is detected, the AI doesn’t just send an alert; it can schedule a repair, order replacement parts, and even reroute production if needed. This reduces downtime and prevents costly disruptions before they happen.

2. Supply chain coordination

Manufacturing supply chains involve dozens (or hundreds) of moving parts. Agentic AI can track supplier performance, monitor delivery schedules, anticipate bottlenecks, and automatically adjust orders or logistics to avoid delays.

For instance, if a shipment is delayed at customs, an AI agent might shift resources, notify production teams, and reorder from an alternate supplier, keeping everything on track with minimal manual input.

3. Quality control and inspection

AI agents can be used on the factory floor to oversee product quality in real time. They can analyse images, sensor data, or production logs to detect defects, spot anomalies, and flag items that don’t meet standards.

4. Energy efficiency and sustainability

Agentic AI can also help manufacturers reduce waste and energy use. By analysing real-time consumption data, it can optimise machine usage, turn off idle equipment, and adjust environmental controls (like lighting or HVAC) for better efficiency.

Over time, these agents can learn patterns, suggest long-term changes, and even track progress toward sustainability goals.

Customer support

Customer support is one of the most visible and high-impact areas where agentic AI is making a difference. 

1. End-to-end ticket resolution

AI agents can identify the nature of a support request, retrieve relevant data from internal systems (like order details, delivery status, or user history), and carry out actions like issuing refunds, updating addresses, or cancelling subscriptions without human input.

2. Proactive customer engagement

Agentic AI can spot potential issues before the customer even notices them. For example, if a product shipment is delayed, an AI agent can detect the delay, notify the customer, offer a solution (like a discount or replacement), and log the interaction automatically.

This kind of proactive support builds trust and reduces inbound tickets, since problems are addressed before they escalate.

3. Intelligent routing and escalation

When an issue does need a human touch, agentic AI doesn’t just pass it on blindly. It can evaluate the context, prioritise the urgency, and route the request to the right agent or team, along with all the background info they’ll need.

4. Learning and adapting over time

Unlike traditional chatbots that follow fixed scripts, agentic AI learns from every interaction. It refines how it communicates, which solutions work best, and how to handle similar requests better next time.

It’s not just answering tickets, it’s improving the customer experience with every case it handles.

5. Multi-channel support integration

Agentic AI can operate across channels: email, chat, SMS, even voice, and maintain context as it moves between them. A customer might start a conversation via chat, switch to email, and still get a consistent, personalised experience because the AI keeps the thread intact and understands the full history.

Education and training

AI agents do more than just deliver information; they guide learners, personalise their journey, and handle behind-the-scenes tasks that free up educators to focus on what matters most: teaching and mentorship.

1. Personalised learning paths

Agentic AI can tailor the learning experience to each student’s pace, strengths, and gaps. Instead of serving the same content to everyone, an AI agent can assess a learner’s progress in real time, adjust the difficulty level, suggest supplementary resources, and even change the learning format based on how the student responds.

This kind of adaptive learning keeps students engaged and helps them master topics more effectively, whether in schools, universities, or corporate training environments.

2. Intelligent tutoring and feedback

AI agents can act as always-available tutors, answering questions, explaining difficult concepts, and offering practice exercises personalised to the learner’s needs. They can also provide detailed, instant feedback on assignments or quizzes, highlighting what was done well and where improvement is needed.

3. Administrative automation for educators

Teachers and trainers often spend a large chunk of time on non-teaching tasks like grading, tracking attendance, scheduling, and reporting. Agentic AI can step in to automate much of this work. 

For instance, an agent might grade assignments, identify students who are falling behind, notify them with reminders, and update dashboards for teachers. This gives educators more time to focus on engaging with students, planning lessons, and supporting individual learning needs.

4. Corporate training and skills development

In workplace learning, agentic AI is being used to guide employees through training programs based on their roles, goals, and performance. An AI agent can onboard a new employee, assign training modules, track their progress, adjust the plan as needed, and follow up with additional resources or certifications without a human coordinator.

Emerging use cases of agentic AI

While agentic AI is already transforming major industries, we’re also seeing exciting new use cases emerge. Here are a few of the most promising:

AI product managers for internal tools or low-code environments

Managing internal tools and low-code platforms can quickly become a full-time job, especially in large organisations. Agentic AI is stepping in as a kind of AI product manager that monitors tool usage, identifies inefficiencies, gathers user feedback, and even suggests or implements improvements.

For example, an AI agent might detect that a particular team isn’t using a dashboard as intended. It can analyse why, redesign parts of the UI, and notify the team, automating the product iteration cycle. In low-code platforms, the agent can build or modify workflows based on user goals, without needing manual configuration. 

Workflow orchestration in enterprise environments

Enterprises often juggle dozens of systems and processes, many of which depend on each other. Agentic AI can act as a workflow orchestrator, managing complex sequences across departments and software platforms.

For instance, launching a new product might require updates to sales systems, marketing assets, inventory databases, and customer portals. Instead of assigning a human project manager to coordinate it all, an AI agent can track dependencies, trigger actions in the correct order, handle delays or errors, and report progress to stakeholders.

Cybersecurity agents identifying and neutralising threats

Cybersecurity is no longer just about monitoring dashboards; it requires fast, intelligent responses to constantly evolving threats. Agentic AI is starting to play the role of an autonomous security agent that doesn’t just detect anomalies, but actively investigates and responds.

When a suspicious login or unusual network behaviour is detected, an AI agent can trace the activity, isolate affected systems, apply patches, revoke access, and generate a detailed report for the security team. All of this can happen in seconds, far faster than any human-led response.

How GoodCore can help with agentic AI solutions

Agentic AI opens up exciting new possibilities, but building and deploying these systems requires the right mix of strategy, technical expertise, and understanding of your business needs. That’s where GoodCore comes in. We help companies unlock the potential of agentic AI through custom-built solutions that are practical, scalable, and aligned with real-world goals.

Here’s how we can support your journey:

• Custom AI agent development: We design and build intelligent agents tailored to your specific workflows, systems, and business logic.
• Integration with existing systems: Our team ensures seamless integration of AI agents with your current tools, APIs, and data sources.
• Use case discovery & strategy: We work with you to identify high-impact opportunities for agentic AI within your operations.
• Domain expertise: Whether you’re in healthcare, fintech, logistics, or education, our cross-industry experience helps bridge tech with strategy.
• Security & compliance: We build systems with secure, ethical, and regulation-aligned foundations.
• AI + human synergy: Our solutions ensure humans stay in the loop, agents augment human capabilities, not replace them.
• Proof-of-concepts & pilots: Explore Agentic AI with low-risk POCs before scaling across your organisation.
• Ongoing support & optimisation: We don’t stop at deployment, our team helps you monitor, maintain, and continuously improve your AI agents over time.